ArticleBMC bioinformatics2008
SIGffRid: a tool to search for sigma factor binding sites in bacterial genomes using comparative approach and biologically driven statistics.
Article in BMC bioinformatics, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed, 22 citations in OpenAlex.
- Regulatory orchestration of FK506 biosynthesis iniScience · 2025Article
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- iProm-Sigma54: A CNN Base Prediction Tool forCells · 2023Article
- Genome-scale analysis of genetic regulatory elements in Streptomyces avermitilis MA-4680 using transcript boundary information.BMC genomics · 2022Article
- Primary transcriptome and translatome analysis determines transcriptional and translational regulatory elements encoded in the Streptomyces clavuligerus genome.Nucleic acids research · 2019Article
- dRNA-seq transcriptional profiling of the FK506 biosynthetic gene cluster in Streptomyces tsukubaensis NRRL18488 and general analysis of the transcriptome.RNA biology · 2017Article
- The dynamic transcriptional and translational landscape of the model antibiotic producer Streptomyces coelicolor A3(2).Nature communications · 2016Article
- Comparative proteomic analysis of Streptomyces lividans Wild-Type and ppk mutant strains reveals the importance of storage lipids for antibiotic biosynthesis.Applied and environmental microbiology · 2013Article
- Characterizing the interplay between multiple levels of organization within bacterial sigma factor regulatory networks.Nature communications · 2013Article
- Extracting regulator activity profiles by integration of de novo motifs and expression data: characterizing key regulators of nutrient depletion responses in Streptomyces coelicolor.Nucleic acids research · 2012Article
- Reverse biological engineering of hrdB to enhance the production of avermectins in an industrial strain of Streptomyces avermitilis.Proceedings of the National Academy of Sciences of the United States of America · 2010Article
- Mechanisms and evolution of control logic in prokaryotic transcriptional regulation.Microbiology and molecular biology reviews : MMBR · 2009Review
- Statistical tests to compare motif count exceptionalities.BMC bioinformatics · 2007Article
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Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMany programs have been developed to identify transcription factor binding sites. However, most of them are not able to infer two-word motifs with variable spacer lengths. This case is encountered for RNA polymerase Sigma (sigma) Factor Binding Sites (SFBSs) usually composed of two boxes, called -35 and -10 in reference to the transcription initiation point. Our goal is to design an algorithm detecting SFBS by using combinational and statistical constraints deduced from biological observations.
resultsWe describe a new approach to identify SFBSs by comparing two related bacterial genomes. The method, named SIGffRid (SIGma Factor binding sites Finder using R'MES to select Input Data), performs a simultaneous analysis of pairs of promoter regions of orthologous genes. SIGffRid uses a prior identification of over-represented patterns in whole genomes as selection criteria for potential -35 and -10 boxes. These patterns are then grouped using pairs of short seeds (of which one is possibly gapped), allowing a variable-length spacer between them. Next, the motifs are extended guided by statistical considerations, a feature that ensures a selection of motifs with statistically relevant properties. We applied our method to the pair of related bacterial genomes of Streptomyces coelicolor and Streptomyces avermitilis. Cross-check with the well-defined SFBSs of the SigR regulon in S. coelicolor is detailed, validating the algorithm. SFBSs for HrdB and BldN were also found; and the results suggested some new targets for these sigma factors. In addition, consensus motifs for BldD and new SFBSs binding sites were defined, overlapping previously proposed consensuses. Relevant tests were carried out also on bacteria with moderate GC content (i.e. Escherichia coli/Salmonella typhimurium and Bacillus subtilis/Bacillus licheniformis pairs). Motifs of house-keeping sigma factors were found as well as other SFBSs such as that of SigW in Bacillus strains.
conclusionWe demonstrate that our approach combining statistical and biological criteria was successful to predict SFBSs. The method versatility authorizes the recognition of other kinds of two-box regulatory sites.
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